This invention relates to producing diffusion magnetic resonance (DMR) images and, in particular, to compensating for effects of eddy currents.
Magnetic resonance imaging (MRI) applies a strong static magnetic field, a radio frequency (RF) magnetic field and time varying magnetic field gradients to an object to be imaged. These fields cause precession of the nuclear spins in the molecules of the object. The nuclear spins, e.g., hydrogen nuclei in water molecules, behave in a predictable manner in response to the magnetic fields applied by the static, RF and gradient fields. For example, the gradient fields (produced by three orthogonal coils around the object) spatially encode the nuclear spins. The precessing nuclear spins emit RF signals that are detected and analyzed by the MRI system to reconstruct an image of the object.
Many techniques have been developed to acquire magnetic resonance (MR) images. These techniques apply various magnetic gradient pulses and RF pulses to manipulate nuclear spins to achieve desired imaging time, image contrast, resolutions and other image characteristics. Two closely related techniques that have been increasingly used are diffusion weighted imaging (DWI) and diffusion tensor imaging (DTI). In what follows, we will refer to them as simply diffusion MRI (DMRI).
In DMRI, pulse sequences are applied to provide contrast between molecules having different degrees of random movement. Diffusion-weighting gradients enhance the signal differences due to variations in diffusivity of the molecules in the object being imaged. The signal differences are used to generate images with diffusion contrast. In proton MRI, DMRI images depict differences in water molecular diffusion.
A problem associated with DMRI is the effect of eddy currents induced by the strong diffusion-weighting gradient pulses. DMRI relies on measurements in which the direction and/or strength of diffusion-weighting gradient pulses are varied. DMRI sequences tend to apply gradient lobes having high amplitudes that create eddy currents in the MRI hardware. These eddy currents are disadvantageous in that they adversely influence the acquired MR imaging data, and consequently cause image distortions that depend on the strength and orientation of the diffusion-weighting gradient pulses.
Prior methods to address the effects of eddy currents induced by strong diffusion-weighting gradient pulses can generally be categorized as (1) post acquisition corrections and (2) DMRI sequence modification. In the first category, some form of image correction is applied post image data acquisition to correct for eddy current artifacts in the acquired image data. Geometrical corrections are performed by image registration or by pre-mapping the eddy currents. Though post acquisition correction by image registration does not require a detailed knowledge about the eddy currents, the robustness and quality of such correction procedures are often limited by the particular algorithm used. Further, post-acquisition correction is often compromised by image distortions caused by effects other than eddy currents. In addition, eddy currents often produce signal losses that cannot be easily corrected by post acquisition procedures.
In the second category, a DMRI sequence is modified to reduce eddy currents produced by the diffusion-weighting gradient pulses or to diminish the effects of eddy currents on the images. Modifying DMRI sequences to counter the effects of the eddy currents has been problematic. For example, double-spin echoes have been applied to reduce eddy currents. However, reduction of eddy currents by generating double spin-echoes has the undesired side effect of prolonging the DMRI sequences and requires more gradient switching. In addition, calibration techniques have been applied in attempts to fully characterize eddy currents produced by the diffusion-weighting gradient pulses. Using calibration information for a MRI system, the effects of eddy currents within a DMRI sequence are predicted and the DMRI sequence is modified to null or reduce the effects of the eddy currents, such as by introducing gradient offsets. However, characterization of eddy currents based on calibration information does not fully predict the eddy currents induced within the DMRI sequences that will actually be used for imaging. Further, the eddy current characterization is most accurate at the time when the calibration procedure is performed and becomes less and less accurate as the characteristics of the MRI system change in time. Moreover, eddy currents induced by the diffusion-weighting gradient pulses depend on the orientation and strength of the gradients, as well as on the timing of the DMRI sequence and on how the sequence events are interleaved. Accordingly, it is difficult to fully characterize the eddy currents ahead of time that reflect what truly occur post-calibration during any DMRI sequence.
In view of the difficulties with prior eddy current compensation techniques (especially those that modify the DMRI sequence), there remains a long-felt need for pre-scan techniques that can easily and quickly measure and compensate for the effects of the eddy currents induced by diffusion-weighting gradient pulses within a DMRI sequence.